Readiness to embrace artificial intelligence amongst medical doctors and students (Preprint)

BACKGROUND Similar to understanding how blood pressure is measured by a sphygmomanometer, physicians will soon have to understand how an Artificial Intelligence-based application has come to the conclusion that a patient suffers from hypertension, diabetes, or cancer. Though there is an increasing number of use cases where artificial intelligence is or can be applied to improve medical outcomes, the extent to which medical doctors and students are ready to work and leverage this paradigm is unclear. OBJECTIVE This research aims to capture medical students and doctors’ level of familiarity towards artificial intelligence in medicine as well as their challenges, barriers, and potential risks linked to the democratization of this new paradigm. METHODS An online questionnaire comprising five dimensions – demographics, concepts and definitions, training and education, implementation, and risks - was systematically designed from a literature search. It was filled in by 207 medical doctors and medical students trained in all continents with a majority of them in Europe, Middle East, Asia and North America. RESULTS Results revealed no significant difference in the familiarity of artificial intelligence between medical doctors and students (p-value=0.91), except that medical students perceived artificial intelligence in medicine to lead to higher risks for patients and the field of medicine in general (p-value=0.0006). We also identified a rather low level of familiarity with artificial intelligence (medical student=2.11/5; medical doctors=2.06/5) as well as a low attendance to education or training. Only 3/105 medical doctors attended a course on artificial intelligence within the last year compared to 10/102 medical students. Complexity of the field of medicine was considered as one of the biggest challenges (medical doctors=3.5/5; medical students 3.8/5) while the reduction of physicians’ skills the most important risk (medical doctors=3.3; medical students=3.6; p-value=0.031). CONCLUSIONS The question is not whether artificial intelligence will be used in medicine, but when it will become a standard practice for optimizing healthcare. The low level of familiarity with artificial intelligence identified in this study calls for the implementation of specific education and training in medical schools and hospitals to ensure that medical professionals can leverage this new paradigm and improve health outcomes.